Glassdoor Salaries

Dataset statistics

Number of variables	25
Number of observations	742
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	275
Duplicate rows (%)	37.1%
Total size in memory	674.0 KiB
Average record size in memory	930.2 B

Variable types

CAT	11
BOOL	8
NUM	6

Reproduction

Analysis started	2020-06-19 04:19:48.236762
Analysis finished	2020-06-19 04:20:02.085298
Duration	13.85 seconds
Version	pandas-profiling v2.8.0
Command line	`pandas_profiling --config_file config.yaml [YOUR_FILE.csv]`
Download configuration	config.yaml

Warnings

Dataset has 275 (37.1%) duplicate rows	Duplicates
`Job Title` has a high cardinality: 264 distinct values	High cardinality
`Location` has a high cardinality: 200 distinct values	High cardinality
`Headquarters` has a high cardinality: 198 distinct values	High cardinality
`Industry` has a high cardinality: 60 distinct values	High cardinality
`Competitors` has a high cardinality: 128 distinct values	High cardinality
`company_txt` has a high cardinality: 343 distinct values	High cardinality
`max_salary` is highly correlated with `min_salary` and 1 other fields	High correlation
`min_salary` is highly correlated with `max_salary` and 1 other fields	High correlation
`avg_salary` is highly correlated with `min_salary` and 1 other fields	High correlation
`Sector` is highly correlated with `Industry`	High correlation
`Industry` is highly correlated with `Sector`	High correlation

Job Title
Categorical

HIGH CARDINALITY

Distinct count	264
Unique (%)	35.6%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

Data Scientist	131
Data Engineer	53
Senior Data Scientist	34
Data Analyst	15
Senior Data Engineer	14
Other values (259)	495

Value	Count	Frequency (%)
Data Scientist	131	17.7%
Data Engineer	53	7.1%
Senior Data Scientist	34	4.6%
Data Analyst	15	2.0%
Senior Data Engineer	14	1.9%
Senior Data Analyst	12	1.6%
Lead Data Scientist	8	1.1%
Sr. Data Engineer	6	0.8%
Marketing Data Analyst	6	0.8%
Machine Learning Engineer	5	0.7%
Principal Data Scientist	5	0.7%
MED TECH/LAB SCIENTIST- SOUTH COASTAL LAB	4	0.5%
Research Scientist	4	0.5%
Food Scientist - Developer	4	0.5%
Staff Scientist-Downstream Process Development	4	0.5%
R&D Specialist/ Food Scientist	4	0.5%
Sr. Data Engineer - Contract-to-Hire (Java)	4	0.5%
Senior Research Scientist-Machine Learning	4	0.5%
Medical Laboratory Scientist	4	0.5%
Analytics Manager - Data Mart	4	0.5%
Senior Data Scientist - R&D Oncology	3	0.4%
Research Scientist, Immunology - Cancer Biology	3	0.4%
Revenue Analytics Manager	3	0.4%
Lead Data Engineer	3	0.4%
Senior Scientist (Neuroscience)	3	0.4%
Other values (239)	402	54.2%

Length

Max length	98
Median length	23
Mean length	27.94204852
Min length	9

Overview of Unicode Properties

Unique unicode characters	66
Unique unicode categories (?)	9
Unique unicode scripts (?)	2
Unique unicode blocks (?)	2

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
t	2114	10.2%
	2081	10.0%
a	2004	9.7%
i	1852	8.9%
e	1744	8.4%
n	1605	7.7%
c	940	4.5%
s	938	4.5%
r	857	4.1%
S	799	3.9%
D	661	3.2%
o	641	3.1%
l	532	2.6%
g	374	1.8%
A	290	1.4%
y	287	1.4%
E	261	1.3%
-	184	0.9%
u	175	0.8%
m	168	0.8%
M	151	0.7%
I	150	0.7%
d	139	0.7%
C	136	0.7%
p	123	0.6%
Other values (41)	1527	7.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	14912	71.9%
Uppercase Letter	3194	15.4%
Space Separator	2081	10.0%
Other Punctuation	228	1.1%
Dash Punctuation	193	0.9%
Open Punctuation	42	0.2%
Decimal Number	41	0.2%
Close Punctuation	41	0.2%
Math Symbol	1	< 0.1%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
S	799	25.0%
D	661	20.7%
A	290	9.1%
E	261	8.2%
M	151	4.7%
I	150	4.7%
C	136	4.3%
L	118	3.7%
P	111	3.5%
R	102	3.2%
T	90	2.8%
B	66	2.1%
O	56	1.8%
N	48	1.5%
H	36	1.1%
G	22	0.7%
F	22	0.7%
V	21	0.7%
U	17	0.5%
Q	14	0.4%
W	7	0.2%
J	7	0.2%
Y	5	0.2%
K	4	0.1%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
t	2114	14.2%
a	2004	13.4%
i	1852	12.4%
e	1744	11.7%
n	1605	10.8%
c	940	6.3%
s	938	6.3%
r	857	5.7%
o	641	4.3%
l	532	3.6%
g	374	2.5%
y	287	1.9%
u	175	1.2%
m	168	1.1%
d	139	0.9%
p	123	0.8%
h	121	0.8%
f	103	0.7%
v	76	0.5%
b	35	0.2%
k	32	0.2%
w	26	0.2%
x	11	0.1%
j	8	0.1%
z	7	< 0.1%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	2081	100.0%

Most frequent Dash Punctuation characters

Value	Count	Frequency (%)
-	184	95.3%
–	9	4.7%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
,	103	45.2%
/	62	27.2%
.	35	15.4%
&	26	11.4%
:	2	0.9%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
2	14	34.1%
0	12	29.3%
1	8	19.5%
4	3	7.3%
9	2	4.9%
5	2	4.9%

Most frequent Open Punctuation characters

Value	Count	Frequency (%)
(	42	100.0%

Most frequent Close Punctuation characters

Value	Count	Frequency (%)
)	41	100.0%

Most frequent Math Symbol characters

Value	Count	Frequency (%)
\|	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	18106	87.3%
Common	2627	12.7%

Most frequent Latin characters

Value	Count	Frequency (%)
t	2114	11.7%
a	2004	11.1%
i	1852	10.2%
e	1744	9.6%
n	1605	8.9%
c	940	5.2%
s	938	5.2%
r	857	4.7%
S	799	4.4%
D	661	3.7%
o	641	3.5%
l	532	2.9%
g	374	2.1%
A	290	1.6%
y	287	1.6%
E	261	1.4%
u	175	1.0%
m	168	0.9%
M	151	0.8%
I	150	0.8%
d	139	0.8%
C	136	0.8%
p	123	0.7%
h	121	0.7%
L	118	0.7%
Other values (24)	926	5.1%

Most frequent Common characters

Value	Count	Frequency (%)
	2081	79.2%
-	184	7.0%
,	103	3.9%
/	62	2.4%
(	42	1.6%
)	41	1.6%
.	35	1.3%
&	26	1.0%
2	14	0.5%
0	12	0.5%
–	9	0.3%
1	8	0.3%
4	3	0.1%
9	2	0.1%
5	2	0.1%
:	2	0.1%
\|	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	20724	> 99.9%
Punctuation	9	< 0.1%

Most frequent ASCII characters

Value	Count	Frequency (%)
t	2114	10.2%
	2081	10.0%
a	2004	9.7%
i	1852	8.9%
e	1744	8.4%
n	1605	7.7%
c	940	4.5%
s	938	4.5%
r	857	4.1%
S	799	3.9%
D	661	3.2%
o	641	3.1%
l	532	2.6%
g	374	1.8%
A	290	1.4%
y	287	1.4%
E	261	1.3%
-	184	0.9%
u	175	0.8%
m	168	0.8%
M	151	0.7%
I	150	0.7%
d	139	0.7%
C	136	0.7%
p	123	0.6%
Other values (40)	1518	7.3%

Most frequent Punctuation characters

Value	Count	Frequency (%)
–	9	100.0%

Rating
Real number (ℝ)

Distinct count	31
Unique (%)	4.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	3.6188679245283017
Minimum	-1.0
Maximum	5.0
Zeros	0
Zeros (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	-1
5-th percentile	2.6
Q1	3.3
median	3.7
Q3	4
95-th percentile	4.7
Maximum	5
Range	6
Interquartile range (IQR)	0.7

Descriptive statistics

Standard deviation	0.8012101585
Coefficient of variation (CV)	0.2213980104
Kurtosis	14.30412724
Mean	3.618867925
Median Absolute Deviation (MAD)	0.35
Skewness	-2.814019554
Sum	2685.2
Variance	0.641937718

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
3.9	63	8.5%
3.8	61	8.2%
3.7	61	8.2%
3.5	49	6.6%
4	47	6.3%
3.6	46	6.2%
3.4	44	5.9%
3.3	39	5.3%
3.2	35	4.7%
4.4	33	4.4%
4.3	32	4.3%
4.7	31	4.2%
4.2	26	3.5%
3.1	25	3.4%
4.1	19	2.6%
2.9	18	2.4%
3	17	2.3%
2.7	14	1.9%
2.6	12	1.6%
-1	11	1.5%
4.6	10	1.3%
4.8	9	1.2%
2.8	7	0.9%
2.4	7	0.9%
4.5	7	0.9%
Other values (6)	19	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1	11	1.5%
1.9	3	0.4%
2.1	5	0.7%
2.2	2	0.3%
2.3	2	0.3%
2.4	7	0.9%
2.5	2	0.3%
2.6	12	1.6%
2.7	14	1.9%
2.8	7	0.9%

Value	Count	Frequency (%)
5	5	0.7%
4.8	9	1.2%
4.7	31	4.2%
4.6	10	1.3%
4.5	7	0.9%
4.4	33	4.4%
4.3	32	4.3%
4.2	26	3.5%
4.1	19	2.6%
4	47	6.3%

Location
Categorical

HIGH CARDINALITY

Distinct count	200
Unique (%)	27.0%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

New York, NY	55
San Francisco, CA	49
Cambridge, MA	47
Chicago, IL	32
Boston, MA	23
Other values (195)	536

Value	Count	Frequency (%)
New York, NY	55	7.4%
San Francisco, CA	49	6.6%
Cambridge, MA	47	6.3%
Chicago, IL	32	4.3%
Boston, MA	23	3.1%
San Jose, CA	13	1.8%
Pittsburgh, PA	12	1.6%
Rockville, MD	11	1.5%
Washington, DC	11	1.5%
Richland, WA	10	1.3%
Winston-Salem, NC	10	1.3%
Herndon, VA	10	1.3%
Indianapolis, IN	9	1.2%
San Diego, CA	9	1.2%
South San Francisco, CA	8	1.1%
Austin, TX	8	1.1%
Mountain View, CA	8	1.1%
Palo Alto, CA	7	0.9%
Rochester, NY	7	0.9%
Phoenix, AZ	6	0.8%
Marlborough, MA	6	0.8%
Salt Lake City, UT	6	0.8%
Huntsville, AL	6	0.8%
Gaithersburg, MD	6	0.8%
Charlotte, NC	6	0.8%
Other values (175)	367	49.5%

Length

Max length	33
Median length	13
Mean length	13.1509434
Min length	8

Overview of Unicode Properties

Unique unicode characters	54
Unique unicode categories (?)	5
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
	992	10.2%
,	743	7.6%
a	607	6.2%
o	533	5.5%
n	529	5.4%
e	514	5.3%
i	493	5.1%
A	438	4.5%
r	424	4.3%
l	348	3.6%
C	336	3.4%
t	320	3.3%
s	276	2.8%
c	228	2.3%
N	211	2.2%
M	202	2.1%
g	178	1.8%
h	172	1.8%
d	158	1.6%
S	153	1.6%
Y	133	1.4%
u	128	1.3%
L	106	1.1%
m	105	1.1%
k	105	1.1%
Other values (29)	1326	13.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5525	56.6%
Uppercase Letter	2488	25.5%
Space Separator	992	10.2%
Other Punctuation	743	7.6%
Dash Punctuation	10	0.1%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
A	438	17.6%
C	336	13.5%
N	211	8.5%
M	202	8.1%
S	153	6.1%
Y	133	5.3%
L	106	4.3%
F	93	3.7%
I	89	3.6%
D	87	3.5%
P	84	3.4%
W	72	2.9%
B	61	2.5%
V	61	2.5%
T	60	2.4%
H	58	2.3%
R	56	2.3%
O	56	2.3%
J	35	1.4%
X	28	1.1%
G	17	0.7%
K	15	0.6%
E	15	0.6%
U	10	0.4%
Z	9	0.4%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
a	607	11.0%
o	533	9.6%
n	529	9.6%
e	514	9.3%
i	493	8.9%
r	424	7.7%
l	348	6.3%
t	320	5.8%
s	276	5.0%
c	228	4.1%
g	178	3.2%
h	172	3.1%
d	158	2.9%
u	128	2.3%
m	105	1.9%
k	105	1.9%
b	102	1.8%
w	91	1.6%
v	68	1.2%
p	53	1.0%
y	43	0.8%
f	24	0.4%
x	18	0.3%
q	6	0.1%
j	2	< 0.1%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
,	743	100.0%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	992	100.0%

Most frequent Dash Punctuation characters

Value	Count	Frequency (%)
-	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	8013	82.1%
Common	1745	17.9%

Most frequent Latin characters

Value	Count	Frequency (%)
a	607	7.6%
o	533	6.7%
n	529	6.6%
e	514	6.4%
i	493	6.2%
A	438	5.5%
r	424	5.3%
l	348	4.3%
C	336	4.2%
t	320	4.0%
s	276	3.4%
c	228	2.8%
N	211	2.6%
M	202	2.5%
g	178	2.2%
h	172	2.1%
d	158	2.0%
S	153	1.9%
Y	133	1.7%
u	128	1.6%
L	106	1.3%
m	105	1.3%
k	105	1.3%
b	102	1.3%
F	93	1.2%
Other values (26)	1121	14.0%

Most frequent Common characters

Value	Count	Frequency (%)
	992	56.8%
,	743	42.6%
-	10	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	9758	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
	992	10.2%
,	743	7.6%
a	607	6.2%
o	533	5.5%
n	529	5.4%
e	514	5.3%
i	493	5.1%
A	438	4.5%
r	424	4.3%
l	348	3.6%
C	336	3.4%
t	320	3.3%
s	276	2.8%
c	228	2.3%
N	211	2.2%
M	202	2.1%
g	178	1.8%
h	172	1.8%
d	158	1.6%
S	153	1.6%
Y	133	1.4%
u	128	1.3%
L	106	1.1%
m	105	1.1%
k	105	1.1%
Other values (29)	1326	13.6%

Headquarters
Categorical

HIGH CARDINALITY

Distinct count	198
Unique (%)	26.7%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

New York, NY	52
San Francisco, CA	42
Chicago, IL	30
Cambridge, MA	20
Winston-Salem, NC	14
Other values (193)	584

Value	Count	Frequency (%)
New York, NY	52	7.0%
San Francisco, CA	42	5.7%
Chicago, IL	30	4.0%
Cambridge, MA	20	2.7%
Winston-Salem, NC	14	1.9%
Boston, MA	14	1.9%
OSAKA, Japan	14	1.9%
Springfield, MA	14	1.9%
Reston, VA	12	1.6%
Richland, WA	12	1.6%
Pittsburgh, PA	11	1.5%
Mountain View, CA	11	1.5%
Palo Alto, CA	10	1.3%
Cambridge, United Kingdom	9	1.2%
Salt Lake City, UT	9	1.2%
Washington, DC	9	1.2%
Denver, CO	8	1.1%
San Jose, CA	8	1.1%
Rockville, MD	8	1.1%
Bedford, MA	8	1.1%
Herndon, VA	8	1.1%
San Rafael, CA	7	0.9%
Chadds Ford, PA	7	0.9%
Basel, Switzerland	7	0.9%
Rochester, NY	7	0.9%
Other values (173)	391	52.7%

Length

Max length	26
Median length	13
Mean length	13.606469
Min length	2

Overview of Unicode Properties

Unique unicode characters	55
Unique unicode categories (?)	6
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
	1033	10.2%
,	741	7.3%
a	647	6.4%
n	615	6.1%
e	560	5.5%
o	528	5.2%
i	510	5.1%
A	459	4.5%
r	422	4.2%
l	370	3.7%
C	350	3.5%
t	348	3.4%
s	259	2.6%
d	237	2.3%
c	219	2.2%
N	192	1.9%
S	181	1.8%
M	178	1.8%
g	178	1.8%
h	159	1.6%
Y	115	1.1%
m	114	1.1%
u	111	1.1%
w	110	1.1%
L	107	1.1%
Other values (30)	1353	13.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5779	57.2%
Uppercase Letter	2525	25.0%
Space Separator	1033	10.2%
Other Punctuation	741	7.3%
Dash Punctuation	17	0.2%
Decimal Number	1	< 0.1%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
A	459	18.2%
C	350	13.9%
N	192	7.6%
S	181	7.2%
M	178	7.0%
Y	115	4.6%
L	107	4.2%
F	102	4.0%
I	82	3.2%
P	80	3.2%
V	79	3.1%
W	75	3.0%
D	73	2.9%
B	71	2.8%
R	71	2.8%
O	58	2.3%
T	50	2.0%
J	40	1.6%
K	39	1.5%
H	32	1.3%
U	28	1.1%
X	21	0.8%
G	18	0.7%
E	16	0.6%
Z	5	0.2%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
a	647	11.2%
n	615	10.6%
e	560	9.7%
o	528	9.1%
i	510	8.8%
r	422	7.3%
l	370	6.4%
t	348	6.0%
s	259	4.5%
d	237	4.1%
c	219	3.8%
g	178	3.1%
h	159	2.8%
m	114	2.0%
u	111	1.9%
w	110	1.9%
k	102	1.8%
b	66	1.1%
p	59	1.0%
y	52	0.9%
v	46	0.8%
f	42	0.7%
x	14	0.2%
z	10	0.2%
j	1	< 0.1%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
,	741	100.0%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	1033	100.0%

Most frequent Dash Punctuation characters

Value	Count	Frequency (%)
-	17	100.0%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
1	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	8304	82.3%
Common	1792	17.7%

Most frequent Latin characters

Value	Count	Frequency (%)
a	647	7.8%
n	615	7.4%
e	560	6.7%
o	528	6.4%
i	510	6.1%
A	459	5.5%
r	422	5.1%
l	370	4.5%
C	350	4.2%
t	348	4.2%
s	259	3.1%
d	237	2.9%
c	219	2.6%
N	192	2.3%
S	181	2.2%
M	178	2.1%
g	178	2.1%
h	159	1.9%
Y	115	1.4%
m	114	1.4%
u	111	1.3%
w	110	1.3%
L	107	1.3%
F	102	1.2%
k	102	1.2%
Other values (26)	1131	13.6%

Most frequent Common characters

Value	Count	Frequency (%)
	1033	57.6%
,	741	41.4%
-	17	0.9%
1	1	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10096	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
	1033	10.2%
,	741	7.3%
a	647	6.4%
n	615	6.1%
e	560	5.5%
o	528	5.2%
i	510	5.1%
A	459	4.5%
r	422	4.2%
l	370	3.7%
C	350	3.5%
t	348	3.4%
s	259	2.6%
d	237	2.3%
c	219	2.2%
N	192	1.9%
S	181	1.8%
M	178	1.8%
g	178	1.8%
h	159	1.6%
Y	115	1.1%
m	114	1.1%
u	111	1.1%
w	110	1.1%
L	107	1.1%
Other values (30)	1353	13.4%

Size
Categorical

Distinct count	9
Unique (%)	1.2%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

1001 to 5000 employees	150
501 to 1000 employees	134
10000+ employees	130
201 to 500 employees	117
51 to 200 employees	94
Other values (4)	117

Value	Count	Frequency (%)
1001 to 5000 employees	150	20.2%
501 to 1000 employees	134	18.1%
10000+ employees	130	17.5%
201 to 500 employees	117	15.8%
51 to 200 employees	94	12.7%
5001 to 10000 employees	76	10.2%
1 to 50 employees	31	4.2%
Unknown	9	1.2%
-1	1	0.1%

Length

Max length	23
Median length	20
Mean length	19.7574124
Min length	2

Overview of Unicode Properties

Unique unicode characters	19
Unique unicode categories (?)	6
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
0	2832	19.3%
e	2196	15.0%
	1936	13.2%
o	1343	9.2%
1	1093	7.5%
m	732	5.0%
p	732	5.0%
l	732	5.0%
y	732	5.0%
s	732	5.0%
5	602	4.1%
t	602	4.1%
2	211	1.4%
+	130	0.9%
n	27	0.2%
U	9	0.1%
k	9	0.1%
w	9	0.1%
-	1	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	7846	53.5%
Decimal Number	4738	32.3%
Space Separator	1936	13.2%
Math Symbol	130	0.9%
Uppercase Letter	9	0.1%
Dash Punctuation	1	< 0.1%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
0	2832	59.8%
1	1093	23.1%
5	602	12.7%
2	211	4.5%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	1936	100.0%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
e	2196	28.0%
o	1343	17.1%
m	732	9.3%
p	732	9.3%
l	732	9.3%
y	732	9.3%
s	732	9.3%
t	602	7.7%
n	27	0.3%
k	9	0.1%
w	9	0.1%

Most frequent Math Symbol characters

Value	Count	Frequency (%)
+	130	100.0%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
U	9	100.0%

Most frequent Dash Punctuation characters

Value	Count	Frequency (%)
-	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	7855	53.6%
Common	6805	46.4%

Most frequent Common characters

Value	Count	Frequency (%)
0	2832	41.6%
	1936	28.4%
1	1093	16.1%
5	602	8.8%
2	211	3.1%
+	130	1.9%
-	1	< 0.1%

Most frequent Latin characters

Value	Count	Frequency (%)
e	2196	28.0%
o	1343	17.1%
m	732	9.3%
p	732	9.3%
l	732	9.3%
y	732	9.3%
s	732	9.3%
t	602	7.7%
n	27	0.3%
U	9	0.1%
k	9	0.1%
w	9	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	14660	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
0	2832	19.3%
e	2196	15.0%
	1936	13.2%
o	1343	9.2%
1	1093	7.5%
m	732	5.0%
p	732	5.0%
l	732	5.0%
y	732	5.0%
s	732	5.0%
5	602	4.1%
t	602	4.1%
2	211	1.4%
+	130	0.9%
n	27	0.2%
U	9	0.1%
k	9	0.1%
w	9	0.1%
-	1	< 0.1%

Founded
Real number (ℝ)

Distinct count	102
Unique (%)	13.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1837.154986522911
Minimum	-1
Maximum	2019
Zeros	0
Zeros (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	-1
5-th percentile	-1
Q1	1939
median	1988
Q3	2007
95-th percentile	2014
Maximum	2019
Range	2020
Interquartile range (IQR)	68

Descriptive statistics

Standard deviation	497.1837627
Coefficient of variation (CV)	0.270627011
Kurtosis	9.705374859
Mean	1837.154987
Median Absolute Deviation (MAD)	22
Skewness	-3.394532023
Sum	1363169
Variance	247191.6939

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
-1	50	6.7%
2010	32	4.3%
2008	31	4.2%
1996	27	3.6%
2006	24	3.2%
2012	21	2.8%
2011	19	2.6%
1958	18	2.4%
2007	18	2.4%
2002	18	2.4%
1984	18	2.4%
2015	16	2.2%
2013	15	2.0%
1851	14	1.9%
1875	14	1.9%
1781	14	1.9%
1997	14	1.9%
2014	13	1.8%
1999	12	1.6%
1965	12	1.6%
2017	12	1.6%
2000	10	1.3%
2003	10	1.3%
2005	10	1.3%
1935	10	1.3%
Other values (77)	290	39.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1	50	6.7%
1744	1	0.1%
1781	14	1.9%
1812	1	0.1%
1830	4	0.5%
1846	2	0.3%
1849	7	0.9%
1850	1	0.1%
1851	14	1.9%
1852	5	0.7%

Value	Count	Frequency (%)
2019	2	0.3%
2017	12	1.6%
2016	5	0.7%
2015	16	2.2%
2014	13	1.8%
2013	15	2.0%
2012	21	2.8%
2011	19	2.6%
2010	32	4.3%
2009	6	0.8%

Type of ownership
Categorical

Distinct count	11
Unique (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

Company - Private	410
Company - Public	193
Nonprofit Organization	55
Subsidiary or Business Segment	34
Government	15
Other values (6)	35

Value	Count	Frequency (%)
Company - Private	410	55.3%
Company - Public	193	26.0%
Nonprofit Organization	55	7.4%
Subsidiary or Business Segment	34	4.6%
Government	15	2.0%
Hospital	15	2.0%
College / University	13	1.8%
Other Organization	3	0.4%
School / School District	2	0.3%
-1	1	0.1%
Unknown	1	0.1%

Length

Max length	30
Median length	17
Mean length	17.4245283
Min length	2

Overview of Unicode Properties

Unique unicode characters	37
Unique unicode categories (?)	6
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
	1398	10.8%
a	1178	9.1%
i	921	7.1%
n	888	6.9%
o	857	6.6%
p	673	5.2%
m	652	5.0%
y	650	5.0%
r	624	4.8%
C	616	4.8%
t	607	4.7%
-	604	4.7%
P	603	4.7%
e	584	4.5%
v	438	3.4%
u	261	2.0%
l	238	1.8%
b	227	1.8%
c	199	1.5%
s	166	1.3%
g	105	0.8%
S	72	0.6%
O	61	0.5%
z	58	0.4%
N	55	0.4%
Other values (12)	194	1.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	9424	72.9%
Uppercase Letter	1487	11.5%
Space Separator	1398	10.8%
Dash Punctuation	604	4.7%
Other Punctuation	15	0.1%
Decimal Number	1	< 0.1%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
C	616	41.4%
P	603	40.6%
S	72	4.8%
O	61	4.1%
N	55	3.7%
B	34	2.3%
G	15	1.0%
H	15	1.0%
U	14	0.9%
D	2	0.1%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
a	1178	12.5%
i	921	9.8%
n	888	9.4%
o	857	9.1%
p	673	7.1%
m	652	6.9%
y	650	6.9%
r	624	6.6%
t	607	6.4%
e	584	6.2%
v	438	4.6%
u	261	2.8%
l	238	2.5%
b	227	2.4%
c	199	2.1%
s	166	1.8%
g	105	1.1%
z	58	0.6%
f	55	0.6%
d	34	0.4%
h	7	0.1%
k	1	< 0.1%
w	1	< 0.1%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	1398	100.0%

Most frequent Dash Punctuation characters

Value	Count	Frequency (%)
-	604	100.0%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
/	15	100.0%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
1	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	10911	84.4%
Common	2018	15.6%

Most frequent Latin characters

Value	Count	Frequency (%)
a	1178	10.8%
i	921	8.4%
n	888	8.1%
o	857	7.9%
p	673	6.2%
m	652	6.0%
y	650	6.0%
r	624	5.7%
C	616	5.6%
t	607	5.6%
P	603	5.5%
e	584	5.4%
v	438	4.0%
u	261	2.4%
l	238	2.2%
b	227	2.1%
c	199	1.8%
s	166	1.5%
g	105	1.0%
S	72	0.7%
O	61	0.6%
z	58	0.5%
N	55	0.5%
f	55	0.5%
d	34	0.3%
Other values (8)	89	0.8%

Most frequent Common characters

Value	Count	Frequency (%)
	1398	69.3%
-	604	29.9%
/	15	0.7%
1	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12929	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
	1398	10.8%
a	1178	9.1%
i	921	7.1%
n	888	6.9%
o	857	6.6%
p	673	5.2%
m	652	5.0%
y	650	5.0%
r	624	4.8%
C	616	4.8%
t	607	4.7%
-	604	4.7%
P	603	4.7%
e	584	4.5%
v	438	3.4%
u	261	2.0%
l	238	1.8%
b	227	1.8%
c	199	1.5%
s	166	1.3%
g	105	0.8%
S	72	0.6%
O	61	0.5%
z	58	0.4%
N	55	0.4%
Other values (12)	194	1.5%

Industry
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct count	60
Unique (%)	8.1%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

Biotech & Pharmaceuticals	112
Insurance Carriers	63
Computer Hardware & Software	59
IT Services	50
Health Care Services & Hospitals	49
Other values (55)	409

Value	Count	Frequency (%)
Biotech & Pharmaceuticals	112	15.1%
Insurance Carriers	63	8.5%
Computer Hardware & Software	59	8.0%
IT Services	50	6.7%
Health Care Services & Hospitals	49	6.6%
Enterprise Software & Network Solutions	42	5.7%
Internet	29	3.9%
Consulting	29	3.9%
Advertising & Marketing	25	3.4%
Aerospace & Defense	25	3.4%
Consumer Products Manufacturing	20	2.7%
Research & Development	19	2.6%
Colleges & Universities	16	2.2%
Energy	14	1.9%
Banks & Credit Unions	12	1.6%
Federal Agencies	11	1.5%
Staffing & Outsourcing	10	1.3%
-1	10	1.3%
Real Estate	8	1.1%
Travel Agencies	8	1.1%
Food & Beverage Manufacturing	8	1.1%
Lending	8	1.1%
Financial Analytics & Research	8	1.1%
Security Services	7	0.9%
Department, Clothing, & Shoe Stores	6	0.8%
Other values (35)	94	12.7%

Length

Max length	40
Median length	23
Mean length	21.9083558
Min length	2

Overview of Unicode Properties

Unique unicode characters	52
Unique unicode categories (?)	6
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
e	1784	11.0%
	1406	8.6%
r	1340	8.2%
a	1218	7.5%
t	1048	6.4%
i	982	6.0%
s	969	6.0%
n	848	5.2%
c	763	4.7%
o	746	4.6%
u	501	3.1%
l	435	2.7%
&	416	2.6%
h	329	2.0%
S	313	1.9%
g	276	1.7%
C	267	1.6%
m	253	1.6%
p	217	1.3%
w	204	1.3%
v	201	1.2%
f	182	1.1%
d	166	1.0%
H	159	1.0%
I	157	1.0%
Other values (27)	1076	6.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	12614	77.6%
Uppercase Letter	1774	10.9%
Space Separator	1406	8.6%
Other Punctuation	430	2.6%
Decimal Number	18	0.1%
Dash Punctuation	14	0.1%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
S	313	17.6%
C	267	15.1%
H	159	9.0%
I	157	8.9%
B	151	8.5%
P	143	8.1%
A	98	5.5%
E	79	4.5%
T	78	4.4%
M	73	4.1%
D	51	2.9%
R	45	2.5%
N	44	2.5%
F	33	1.9%
U	28	1.6%
O	17	1.0%
G	14	0.8%
L	12	0.7%
V	5	0.3%
K	4	0.2%
W	3	0.2%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
e	1784	14.1%
r	1340	10.6%
a	1218	9.7%
t	1048	8.3%
i	982	7.8%
s	969	7.7%
n	848	6.7%
c	763	6.0%
o	746	5.9%
u	501	4.0%
l	435	3.4%
h	329	2.6%
g	276	2.2%
m	253	2.0%
p	217	1.7%
w	204	1.6%
v	201	1.6%
f	182	1.4%
d	166	1.3%
k	100	0.8%
y	35	0.3%
b	7	0.1%
z	6	< 0.1%
x	3	< 0.1%
q	1	< 0.1%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	1406	100.0%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
&	416	96.7%
,	14	3.3%

Most frequent Dash Punctuation characters

Value	Count	Frequency (%)
-	14	100.0%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
1	14	77.8%
2	4	22.2%

Most occurring scripts

Value	Count	Frequency (%)
Latin	14388	88.5%
Common	1868	11.5%

Most frequent Latin characters

Value	Count	Frequency (%)
e	1784	12.4%
r	1340	9.3%
a	1218	8.5%
t	1048	7.3%
i	982	6.8%
s	969	6.7%
n	848	5.9%
c	763	5.3%
o	746	5.2%
u	501	3.5%
l	435	3.0%
h	329	2.3%
S	313	2.2%
g	276	1.9%
C	267	1.9%
m	253	1.8%
p	217	1.5%
w	204	1.4%
v	201	1.4%
f	182	1.3%
d	166	1.2%
H	159	1.1%
I	157	1.1%
B	151	1.0%
P	143	1.0%
Other values (21)	736	5.1%

Most frequent Common characters

Value	Count	Frequency (%)
	1406	75.3%
&	416	22.3%
,	14	0.7%
-	14	0.7%
1	14	0.7%
2	4	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	16256	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
e	1784	11.0%
	1406	8.6%
r	1340	8.2%
a	1218	7.5%
t	1048	6.4%
i	982	6.0%
s	969	6.0%
n	848	5.2%
c	763	4.7%
o	746	4.6%
u	501	3.1%
l	435	2.7%
&	416	2.6%
h	329	2.0%
S	313	1.9%
g	276	1.7%
C	267	1.6%
m	253	1.6%
p	217	1.3%
w	204	1.3%
v	201	1.2%
f	182	1.1%
d	166	1.0%
H	159	1.0%
I	157	1.0%
Other values (27)	1076	6.6%

Sector
Categorical

HIGH CORRELATION

Distinct count	25
Unique (%)	3.4%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

Information Technology	180
Biotech & Pharmaceuticals	112
Business Services	97
Insurance	69
Health Care	49
Other values (20)	235

Value	Count	Frequency (%)
Information Technology	180	24.3%
Biotech & Pharmaceuticals	112	15.1%
Business Services	97	13.1%
Insurance	69	9.3%
Health Care	49	6.6%
Finance	42	5.7%
Manufacturing	34	4.6%
Aerospace & Defense	25	3.4%
Education	23	3.1%
Retail	15	2.0%
Oil, Gas, Energy & Utilities	14	1.9%
Government	11	1.5%
-1	10	1.3%
Non-Profit	9	1.2%
Real Estate	8	1.1%
Transportation & Logistics	8	1.1%
Travel & Tourism	8	1.1%
Media	6	0.8%
Telecommunications	6	0.8%
Arts, Entertainment & Recreation	4	0.5%
Consumer Services	4	0.5%
Mining & Metals	3	0.4%
Construction, Repair & Maintenance	3	0.4%
Accounting & Legal	1	0.1%
Agriculture & Forestry	1	0.1%

Length

Max length	34
Median length	17
Mean length	17.02695418
Min length	2

Overview of Unicode Properties

Unique unicode characters	42
Unique unicode categories (?)	6
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
e	1179	9.3%
n	1091	8.6%
o	969	7.7%
a	943	7.5%
i	856	6.8%
c	843	6.7%
	731	5.8%
s	712	5.6%
r	662	5.2%
t	654	5.2%
h	453	3.6%
l	411	3.3%
u	393	3.1%
m	331	2.6%
I	249	2.0%
f	248	2.0%
g	242	1.9%
T	210	1.7%
B	209	1.7%
y	195	1.5%
&	179	1.4%
P	121	1.0%
v	120	0.9%
S	101	0.8%
C	56	0.4%
Other values (17)	476	3.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10367	82.1%
Uppercase Letter	1293	10.2%
Space Separator	731	5.8%
Other Punctuation	214	1.7%
Dash Punctuation	19	0.2%
Decimal Number	10	0.1%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
I	249	19.3%
T	210	16.2%
B	209	16.2%
P	121	9.4%
S	101	7.8%
C	56	4.3%
H	49	3.8%
E	49	3.8%
M	49	3.8%
F	43	3.3%
A	31	2.4%
R	30	2.3%
D	25	1.9%
G	25	1.9%
O	14	1.1%
U	14	1.1%
L	9	0.7%
N	9	0.7%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
e	1179	11.4%
n	1091	10.5%
o	969	9.3%
a	943	9.1%
i	856	8.3%
c	843	8.1%
s	712	6.9%
r	662	6.4%
t	654	6.3%
h	453	4.4%
l	411	4.0%
u	393	3.8%
m	331	3.2%
f	248	2.4%
g	242	2.3%
y	195	1.9%
v	120	1.2%
p	36	0.3%
d	29	0.3%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	731	100.0%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
&	179	83.6%
,	35	16.4%

Most frequent Dash Punctuation characters

Value	Count	Frequency (%)
-	19	100.0%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
1	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	11660	92.3%
Common	974	7.7%

Most frequent Latin characters

Value	Count	Frequency (%)
e	1179	10.1%
n	1091	9.4%
o	969	8.3%
a	943	8.1%
i	856	7.3%
c	843	7.2%
s	712	6.1%
r	662	5.7%
t	654	5.6%
h	453	3.9%
l	411	3.5%
u	393	3.4%
m	331	2.8%
I	249	2.1%
f	248	2.1%
g	242	2.1%
T	210	1.8%
B	209	1.8%
y	195	1.7%
P	121	1.0%
v	120	1.0%
S	101	0.9%
C	56	0.5%
H	49	0.4%
E	49	0.4%
Other values (12)	314	2.7%

Most frequent Common characters

Value	Count	Frequency (%)
	731	75.1%
&	179	18.4%
,	35	3.6%
-	19	2.0%
1	10	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12634	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
e	1179	9.3%
n	1091	8.6%
o	969	7.7%
a	943	7.5%
i	856	6.8%
c	843	6.7%
	731	5.8%
s	712	5.6%
r	662	5.2%
t	654	5.2%
h	453	3.6%
l	411	3.3%
u	393	3.1%
m	331	2.6%
I	249	2.0%
f	248	2.0%
g	242	1.9%
T	210	1.7%
B	209	1.7%
y	195	1.5%
&	179	1.4%
P	121	1.0%
v	120	0.9%
S	101	0.8%
C	56	0.4%
Other values (17)	476	3.8%

Revenue
Categorical

Distinct count	14
Unique (%)	1.9%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

Unknown / Non-Applicable	203
$10+ billion (USD)	124
$100 to $500 million (USD)	91
$1 to $2 billion (USD)	60
$500 million to $1 billion (USD)	57
Other values (9)	207

Value	Count	Frequency (%)
Unknown / Non-Applicable	203	27.4%
$10+ billion (USD)	124	16.7%
$100 to $500 million (USD)	91	12.3%
$1 to $2 billion (USD)	60	8.1%
$500 million to $1 billion (USD)	57	7.7%
$50 to $100 million (USD)	46	6.2%
$25 to $50 million (USD)	40	5.4%
$2 to $5 billion (USD)	39	5.3%
$10 to $25 million (USD)	32	4.3%
$5 to $10 billion (USD)	19	2.6%
$5 to $10 million (USD)	18	2.4%
$1 to $5 million (USD)	8	1.1%
Less than $1 million (USD)	4	0.5%
-1	1	0.1%

Length

Max length	32
Median length	24
Mean length	23.56199461
Min length	2

Overview of Unicode Properties

Unique unicode characters	32
Unique unicode categories (?)	10
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
	2367	13.5%
l	1596	9.1%
o	1411	8.1%
n	1411	8.1%
i	1393	8.0%
$	948	5.4%
0	849	4.9%
U	741	4.2%
(	538	3.1%
S	538	3.1%
D	538	3.1%
)	538	3.1%
b	502	2.9%
1	460	2.6%
t	414	2.4%
p	406	2.3%
5	390	2.2%
m	296	1.7%
a	207	1.2%
e	207	1.2%
-	204	1.2%
k	203	1.2%
w	203	1.2%
/	203	1.2%
N	203	1.2%
Other values (7)	717	4.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	8464	48.4%
Space Separator	2367	13.5%
Uppercase Letter	2227	12.7%
Decimal Number	1870	10.7%
Currency Symbol	948	5.4%
Open Punctuation	538	3.1%
Close Punctuation	538	3.1%
Dash Punctuation	204	1.2%
Other Punctuation	203	1.2%
Math Symbol	124	0.7%

Most frequent Currency Symbol characters

Value	Count	Frequency (%)
$	948	100.0%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
0	849	45.4%
1	460	24.6%
5	390	20.9%
2	171	9.1%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	2367	100.0%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
l	1596	18.9%
o	1411	16.7%
n	1411	16.7%
i	1393	16.5%
b	502	5.9%
t	414	4.9%
p	406	4.8%
m	296	3.5%
a	207	2.4%
e	207	2.4%
k	203	2.4%
w	203	2.4%
c	203	2.4%
s	8	0.1%
h	4	< 0.1%

Most frequent Open Punctuation characters

Value	Count	Frequency (%)
(	538	100.0%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
U	741	33.3%
S	538	24.2%
D	538	24.2%
N	203	9.1%
A	203	9.1%
L	4	0.2%

Most frequent Close Punctuation characters

Value	Count	Frequency (%)
)	538	100.0%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
/	203	100.0%

Most frequent Dash Punctuation characters

Value	Count	Frequency (%)
-	204	100.0%

Most frequent Math Symbol characters

Value	Count	Frequency (%)
+	124	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	10691	61.2%
Common	6792	38.8%

Most frequent Common characters

Value	Count	Frequency (%)
	2367	34.8%
$	948	14.0%
0	849	12.5%
(	538	7.9%
)	538	7.9%
1	460	6.8%
5	390	5.7%
-	204	3.0%
/	203	3.0%
2	171	2.5%
+	124	1.8%

Most frequent Latin characters

Value	Count	Frequency (%)
l	1596	14.9%
o	1411	13.2%
n	1411	13.2%
i	1393	13.0%
U	741	6.9%
S	538	5.0%
D	538	5.0%
b	502	4.7%
t	414	3.9%
p	406	3.8%
m	296	2.8%
a	207	1.9%
e	207	1.9%
k	203	1.9%
w	203	1.9%
N	203	1.9%
A	203	1.9%
c	203	1.9%
s	8	0.1%
L	4	< 0.1%
h	4	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	17483	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
	2367	13.5%
l	1596	9.1%
o	1411	8.1%
n	1411	8.1%
i	1393	8.0%
$	948	5.4%
0	849	4.9%
U	741	4.2%
(	538	3.1%
S	538	3.1%
D	538	3.1%
)	538	3.1%
b	502	2.9%
1	460	2.6%
t	414	2.4%
p	406	2.3%
5	390	2.2%
m	296	1.7%
a	207	1.2%
e	207	1.2%
-	204	1.2%
k	203	1.2%
w	203	1.2%
/	203	1.2%
N	203	1.2%
Other values (7)	717	4.1%

Competitors
Categorical

HIGH CARDINALITY

Distinct count	128
Unique (%)	17.3%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

-1	460
Novartis, Baxter, Pfizer	14
Oak Ridge National Laboratory, National Renewable Energy Lab, Los Alamos National Laboratory	12
Travelers, Allstate, State Farm	10
Roche, GlaxoSmithKline, Novartis	9
Other values (123)	237

Value	Count	Frequency (%)
-1	460	62.0%
Novartis, Baxter, Pfizer	14	1.9%
Oak Ridge National Laboratory, National Renewable Energy Lab, Los Alamos National Laboratory	12	1.6%
Travelers, Allstate, State Farm	10	1.3%
Roche, GlaxoSmithKline, Novartis	9	1.2%
Battelle, General Atomics, SAIC	8	1.1%
Expedia Group, Orbitz Worldwide, Priceline.com	7	0.9%
Pitney Bowes	6	0.8%
Leidos, CACI International, Booz Allen Hamilton	6	0.8%
FLURRY, Chartboost	6	0.8%
Shire, GlaxoSmithKline, Allergan	5	0.7%
Pfizer, AstraZeneca, Merck	4	0.5%
TravelCenters of America, Love's Travel Stops & Country Stores, Wawa	4	0.5%
UDR, AvalonBay Communities, Essex Property Trust	3	0.4%
Munich Re, Hannover RE, SCOR	3	0.4%
Tata Consultancy Services, Accenture, Cognizant Technology Solutions	3	0.4%
See Tickets, TicketWeb, Vendini	3	0.4%
Los Alamos National Laboratory, Battelle, SRI International	3	0.4%
American Express, Mastercard, Discover	3	0.4%
BioMarin Pharmaceutical, Sangamo Therapeutics, bluebird bio	3	0.4%
Seagate Technology, Toshiba	3	0.4%
Credit Karma, LendUp, SoFi	3	0.4%
ManTech, Booz Allen Hamilton, Leidos	3	0.4%
Nationstar Mortgage, Caliber Funding, Quicken Loans	3	0.4%
C.H. Robinson, Total Quality Logistics, Coyote Logistics	3	0.4%
Other values (103)	155	20.9%

Length

Max length	92
Median length	2
Mean length	15.97439353
Min length	2

Overview of Unicode Properties

Unique unicode characters	63
Unique unicode categories (?)	9
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
	1064	9.0%
e	940	7.9%
a	822	6.9%
o	672	5.7%
t	654	5.5%
r	634	5.3%
i	626	5.3%
n	557	4.7%
,	500	4.2%
l	490	4.1%
-	467	3.9%
1	460	3.9%
s	400	3.4%
c	289	2.4%
m	201	1.7%
h	181	1.5%
u	160	1.3%
d	159	1.3%
A	156	1.3%
S	156	1.3%
C	144	1.2%
y	143	1.2%
b	122	1.0%
g	120	1.0%
N	118	1.0%
Other values (38)	1618	13.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	7627	64.3%
Uppercase Letter	1682	14.2%
Space Separator	1064	9.0%
Other Punctuation	541	4.6%
Dash Punctuation	467	3.9%
Decimal Number	462	3.9%
Math Symbol	4	< 0.1%
Open Punctuation	3	< 0.1%
Close Punctuation	3	< 0.1%

Most frequent Dash Punctuation characters

Value	Count	Frequency (%)
-	467	100.0%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
1	460	99.6%
9	2	0.4%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
A	156	9.3%
S	156	9.3%
C	144	8.6%
N	118	7.0%
L	113	6.7%
T	99	5.9%
R	94	5.6%
B	86	5.1%
I	86	5.1%
M	74	4.4%
P	70	4.2%
G	70	4.2%
H	66	3.9%
E	62	3.7%
F	53	3.2%
O	50	3.0%
D	46	2.7%
U	33	2.0%
K	31	1.8%
W	26	1.5%
Y	14	0.8%
Z	9	0.5%
Q	8	0.5%
V	7	0.4%
J	6	0.4%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
e	940	12.3%
a	822	10.8%
o	672	8.8%
t	654	8.6%
r	634	8.3%
i	626	8.2%
n	557	7.3%
l	490	6.4%
s	400	5.2%
c	289	3.8%
m	201	2.6%
h	181	2.4%
u	160	2.1%
d	159	2.1%
y	143	1.9%
b	122	1.6%
g	120	1.6%
v	86	1.1%
p	75	1.0%
k	68	0.9%
f	63	0.8%
z	57	0.7%
x	53	0.7%
w	45	0.6%
q	10	0.1%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	1064	100.0%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
,	500	92.4%
.	19	3.5%
&	13	2.4%
'	9	1.7%

Most frequent Math Symbol characters

Value	Count	Frequency (%)
+	2	50.0%
\|	2	50.0%

Most frequent Open Punctuation characters

Value	Count	Frequency (%)
(	3	100.0%

Most frequent Close Punctuation characters

Value	Count	Frequency (%)
)	3	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	9309	78.5%
Common	2544	21.5%

Most frequent Common characters

Value	Count	Frequency (%)
	1064	41.8%
,	500	19.7%
-	467	18.4%
1	460	18.1%
.	19	0.7%
&	13	0.5%
'	9	0.4%
(	3	0.1%
)	3	0.1%
+	2	0.1%
9	2	0.1%
\|	2	0.1%

Most frequent Latin characters

Value	Count	Frequency (%)
e	940	10.1%
a	822	8.8%
o	672	7.2%
t	654	7.0%
r	634	6.8%
i	626	6.7%
n	557	6.0%
l	490	5.3%
s	400	4.3%
c	289	3.1%
m	201	2.2%
h	181	1.9%
u	160	1.7%
d	159	1.7%
A	156	1.7%
S	156	1.7%
C	144	1.5%
y	143	1.5%
b	122	1.3%
g	120	1.3%
N	118	1.3%
L	113	1.2%
T	99	1.1%
R	94	1.0%
v	86	0.9%
Other values (26)	1173	12.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11853	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
	1064	9.0%
e	940	7.9%
a	822	6.9%
o	672	5.7%
t	654	5.5%
r	634	5.3%
i	626	5.3%
n	557	4.7%
,	500	4.2%
l	490	4.1%
-	467	3.9%
1	460	3.9%
s	400	3.4%
c	289	2.4%
m	201	1.7%
h	181	1.5%
u	160	1.3%
d	159	1.3%
A	156	1.3%
S	156	1.3%
C	144	1.2%
y	143	1.2%
b	122	1.0%
g	120	1.0%
N	118	1.0%
Other values (38)	1618	13.7%

hourly
Boolean

Distinct count	2
Unique (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

0	718
1	24

Frequency Table

Value	Count	Frequency (%)
0	718	96.8%
1	24	3.2%

employer_provided
Boolean

Distinct count	2
Unique (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

0	725
1	17

Frequency Table

Value	Count	Frequency (%)
0	725	97.7%
1	17	2.3%

min_salary
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct count	119
Unique (%)	16.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	74.06873315363882
Minimum	10
Maximum	202
Zeros	0
Zeros (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	10
5-th percentile	32
Q1	52
median	69.5
Q3	91
95-th percentile	127
Maximum	202
Range	192
Interquartile range (IQR)	39

Descriptive statistics

Standard deviation	31.86928207
Coefficient of variation (CV)	0.4302663312
Kurtosis	1.728415099
Mean	74.06873315
Median Absolute Deviation (MAD)	19.5
Skewness	0.9632862889
Sum	54959
Variance	1015.65114

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
65	20	2.7%
80	18	2.4%
61	18	2.4%
81	17	2.3%
63	16	2.2%
74	16	2.2%
86	15	2.0%
56	15	2.0%
52	15	2.0%
49	15	2.0%
60	15	2.0%
43	14	1.9%
54	14	1.9%
42	14	1.9%
71	13	1.8%
44	12	1.6%
68	11	1.5%
100	11	1.5%
110	11	1.5%
50	10	1.3%
83	10	1.3%
39	10	1.3%
76	10	1.3%
75	10	1.3%
64	10	1.3%
Other values (94)	402	54.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
10	2	0.3%
15	2	0.3%
17	2	0.3%
18	4	0.5%
20	1	0.1%
21	8	1.1%
24	3	0.4%
25	3	0.4%
26	1	0.1%
27	3	0.4%

Value	Count	Frequency (%)
202	3	0.4%
200	3	0.4%
190	3	0.4%
176	1	0.1%
171	1	0.1%
158	2	0.3%
150	7	0.9%
139	3	0.4%
138	3	0.4%
136	1	0.1%

max_salary
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct count	163
Unique (%)	22.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	127.18328840970351
Minimum	16
Maximum	306
Zeros	0
Zeros (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	16
5-th percentile	59.1
Q1	96
median	124
Q3	155
95-th percentile	208
Maximum	306
Range	290
Interquartile range (IQR)	59

Descriptive statistics

Standard deviation	46.90900648
Coefficient of variation (CV)	0.3688299545
Kurtosis	0.6089039058
Mean	127.1832884
Median Absolute Deviation (MAD)	29
Skewness	0.4313542674
Sum	94370
Variance	2200.454889

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
140	16	2.2%
119	15	2.0%
124	15	2.0%
110	15	2.0%
127	13	1.8%
113	13	1.8%
86	12	1.6%
101	12	1.6%
173	12	1.6%
85	11	1.5%
139	11	1.5%
62	10	1.3%
142	10	1.3%
160	10	1.3%
134	10	1.3%
112	9	1.2%
123	9	1.2%
133	9	1.2%
99	9	1.2%
97	9	1.2%
149	8	1.1%
143	8	1.1%
105	8	1.1%
129	8	1.1%
132	8	1.1%
Other values (138)	472	63.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
16	1	0.1%
17	2	0.3%
24	2	0.3%
25	5	0.7%
28	3	0.4%
29	2	0.3%
34	6	0.8%
39	4	0.5%
47	1	0.1%
48	2	0.3%

Value	Count	Frequency (%)
306	3	0.4%
289	1	0.1%
275	1	0.1%
272	1	0.1%
250	2	0.3%
239	2	0.3%
238	2	0.3%
231	1	0.1%
228	2	0.3%
224	3	0.4%

avg_salary
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct count	225
Unique (%)	30.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	100.62601078167116
Minimum	13.5
Maximum	254.0
Zeros	0
Zeros (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	13.5
5-th percentile	45.575
Q1	73.5
median	97.5
Q3	122.5
95-th percentile	167.5
Maximum	254
Range	240.5
Interquartile range (IQR)	49

Descriptive statistics

Standard deviation	38.85594816
Coefficient of variation (CV)	0.3861421898
Kurtosis	0.8891961858
Mean	100.6260108
Median Absolute Deviation (MAD)	24.5
Skewness	0.6094736593
Sum	74664.5
Variance	1509.784707

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
87.5	12	1.6%
81	11	1.5%
140	11	1.5%
84.5	10	1.3%
107.5	10	1.3%
85	10	1.3%
107	10	1.3%
120	9	1.2%
87	9	1.2%
70.5	8	1.1%
109	8	1.1%
154.5	8	1.1%
80.5	7	0.9%
121	7	0.9%
85.5	7	0.9%
62.5	7	0.9%
77.5	7	0.9%
114.5	7	0.9%
76.5	7	0.9%
95	7	0.9%
61	7	0.9%
100	7	0.9%
27.5	6	0.8%
54	6	0.8%
94.5	6	0.8%
Other values (200)	538	72.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
13.5	2	0.3%
15.5	1	0.1%
20	1	0.1%
20.5	2	0.3%
21.5	4	0.5%
25	2	0.3%
26.5	3	0.4%
27.5	6	0.8%
29.5	1	0.1%
31.5	3	0.4%

Value	Count	Frequency (%)
254	3	0.4%
237.5	1	0.1%
232.5	1	0.1%
225	2	0.3%
221.5	1	0.1%
205	3	0.4%
194.5	2	0.3%
194	2	0.3%
184.5	2	0.3%
181	3	0.4%

company_txt
Categorical

HIGH CARDINALITY

Distinct count	343
Unique (%)	46.2%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

Reynolds American	14
MassMutual	14
Takeda Pharmaceuticals	14
Software Engineering Institute	11
Liberty Mutual Insurance	10
Other values (338)	679

Value	Count	Frequency (%)
Reynolds American	14	1.9%
MassMutual	14	1.9%
Takeda Pharmaceuticals	14	1.9%
Software Engineering Institute	11	1.5%
Liberty Mutual Insurance	10	1.3%
PNNL	10	1.3%
AstraZeneca	9	1.2%
MITRE	8	1.1%
Pfizer	7	0.9%
Novartis	7	0.9%
Advanced BioScience Laboratories	7	0.9%
Numeric, LLC	7	0.9%
Fareportal	7	0.9%
Rochester Regional Health	7	0.9%
The Church of Jesus Christ of Latter-day Saints	6	0.8%
Tapjoy	6	0.8%
Q2 Solutions	6	0.8%
Novetta	6	0.8%
Beebe Healthcare	6	0.8%
Kronos Bio	6	0.8%
Esri	6	0.8%
Rubius Therapeutics	5	0.7%
Sunovion	5	0.7%
The Hanover Insurance Group	5	0.7%
Autodesk	4	0.5%
Other values (318)	549	74.0%

Length

Max length	52
Median length	14
Mean length	16.22506739
Min length	3

Overview of Unicode Properties

Unique unicode characters	71
Unique unicode categories (?)	8
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
e	1019	8.5%
a	891	7.4%
	767	6.4%
	731	6.1%
n	688	5.7%
t	685	5.7%
i	677	5.6%
r	657	5.5%
o	631	5.2%
s	596	5.0%
c	408	3.4%
l	408	3.4%
u	340	2.8%
h	256	2.1%
C	192	1.6%
d	181	1.5%
S	178	1.5%
m	167	1.4%
g	152	1.3%
T	151	1.3%
A	148	1.2%
p	139	1.2%
y	138	1.1%
I	135	1.1%
L	122	1.0%
Other values (46)	1582	13.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	8433	70.0%
Uppercase Letter	1951	16.2%
Space Separator	767	6.4%
Control	731	6.1%
Other Punctuation	81	0.7%
Decimal Number	54	0.4%
Dash Punctuation	18	0.1%
Math Symbol	4	< 0.1%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
C	192	9.8%
S	178	9.1%
T	151	7.7%
A	148	7.6%
I	135	6.9%
L	122	6.3%
M	117	6.0%
P	111	5.7%
R	109	5.6%
E	94	4.8%
N	87	4.5%
H	80	4.1%
B	77	3.9%
G	65	3.3%
F	54	2.8%
D	36	1.8%
O	32	1.6%
V	29	1.5%
U	24	1.2%
K	24	1.2%
W	21	1.1%
Z	21	1.1%
J	20	1.0%
Q	16	0.8%
Y	5	0.3%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
e	1019	12.1%
a	891	10.6%
n	688	8.2%
t	685	8.1%
i	677	8.0%
r	657	7.8%
o	631	7.5%
s	596	7.1%
c	408	4.8%
l	408	4.8%
u	340	4.0%
h	256	3.0%
d	181	2.1%
m	167	2.0%
g	152	1.8%
p	139	1.6%
y	138	1.6%
v	87	1.0%
f	84	1.0%
b	76	0.9%
k	53	0.6%
w	47	0.6%
x	20	0.2%
z	17	0.2%
j	9	0.1%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	767	100.0%

Most frequent Control characters

Value	Count	Frequency (%)
	731	100.0%

Most frequent Decimal Number characters

Value	Count	Frequency (%)
2	20	37.0%
0	10	18.5%
3	7	13.0%
4	6	11.1%
1	5	9.3%
9	2	3.7%
6	2	3.7%
7	1	1.9%
8	1	1.9%

Most frequent Other Punctuation characters

Value	Count	Frequency (%)
.	37	45.7%
,	21	25.9%
&	13	16.0%
'	8	9.9%
/	2	2.5%

Most frequent Math Symbol characters

Value	Count	Frequency (%)
<	2	50.0%
>	2	50.0%

Most frequent Dash Punctuation characters

Value	Count	Frequency (%)
-	18	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	10384	86.3%
Common	1655	13.7%

Most frequent Latin characters

Value	Count	Frequency (%)
e	1019	9.8%
a	891	8.6%
n	688	6.6%
t	685	6.6%
i	677	6.5%
r	657	6.3%
o	631	6.1%
s	596	5.7%
c	408	3.9%
l	408	3.9%
u	340	3.3%
h	256	2.5%
C	192	1.8%
d	181	1.7%
S	178	1.7%
m	167	1.6%
g	152	1.5%
T	151	1.5%
A	148	1.4%
p	139	1.3%
y	138	1.3%
I	135	1.3%
L	122	1.2%
M	117	1.1%
P	111	1.1%
Other values (27)	1197	11.5%

Most frequent Common characters

Value	Count	Frequency (%)
	767	46.3%
	731	44.2%
.	37	2.2%
,	21	1.3%
2	20	1.2%
-	18	1.1%
&	13	0.8%
0	10	0.6%
'	8	0.5%
3	7	0.4%
4	6	0.4%
1	5	0.3%
/	2	0.1%
<	2	0.1%
>	2	0.1%
9	2	0.1%
6	2	0.1%
7	1	0.1%
8	1	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12039	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
e	1019	8.5%
a	891	7.4%
	767	6.4%
	731	6.1%
n	688	5.7%
t	685	5.7%
i	677	5.6%
r	657	5.5%
o	631	5.2%
s	596	5.0%
c	408	3.4%
l	408	3.4%
u	340	2.8%
h	256	2.1%
C	192	1.6%
d	181	1.5%
S	178	1.5%
m	167	1.4%
g	152	1.3%
T	151	1.3%
A	148	1.2%
p	139	1.2%
y	138	1.1%
I	135	1.1%
L	122	1.0%
Other values (46)	1582	13.1%

job_state
Categorical

Distinct count	38
Unique (%)	5.1%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

CA	151
MA	103
NY	72
VA	41
IL	40
Other values (33)	335

Value	Count	Frequency (%)
CA	151	20.4%
MA	103	13.9%
NY	72	9.7%
VA	41	5.5%
IL	40	5.4%
MD	35	4.7%
PA	33	4.4%
TX	28	3.8%
WA	21	2.8%
NC	21	2.8%
NJ	17	2.3%
FL	16	2.2%
OH	14	1.9%
TN	13	1.8%
DC	11	1.5%
CO	11	1.5%
UT	10	1.3%
WI	10	1.3%
IN	10	1.3%
MO	9	1.2%
AZ	9	1.2%
AL	8	1.1%
DE	6	0.8%
MI	6	0.8%
KY	6	0.8%
Other values (13)	41	5.5%

Length

Max length	12
Median length	3
Mean length	3.01212938
Min length	3

Overview of Unicode Properties

Unique unicode characters	31
Unique unicode categories (?)	3
Unique unicode scripts (?)	2
Unique unicode blocks (?)	1

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

Value	Count	Frequency (%)
	743	33.2%
A	382	17.1%
C	200	8.9%
M	158	7.1%
N	142	6.4%
Y	78	3.5%
I	74	3.3%
L	69	3.1%
T	56	2.5%
D	54	2.4%
V	41	1.8%
O	38	1.7%
P	33	1.5%
W	31	1.4%
X	28	1.3%
J	17	0.8%
F	16	0.7%
H	14	0.6%
E	10	0.4%
U	10	0.4%
K	9	0.4%
Z	9	0.4%
G	6	0.3%
R	5	0.2%
S	4	0.2%
Other values (6)	8	0.4%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1484	66.4%
Space Separator	743	33.2%
Lowercase Letter	8	0.4%

Most frequent Space Separator characters

Value	Count	Frequency (%)
	743	100.0%

Most frequent Uppercase Letter characters

Value	Count	Frequency (%)
A	382	25.7%
C	200	13.5%
M	158	10.6%
N	142	9.6%
Y	78	5.3%
I	74	5.0%
L	69	4.6%
T	56	3.8%
D	54	3.6%
V	41	2.8%
O	38	2.6%
P	33	2.2%
W	31	2.1%
X	28	1.9%
J	17	1.1%
F	16	1.1%
H	14	0.9%
E	10	0.7%
U	10	0.7%
K	9	0.6%
Z	9	0.6%
G	6	0.4%
R	5	0.3%
S	4	0.3%

Most frequent Lowercase Letter characters

Value	Count	Frequency (%)
s	2	25.0%
e	2	25.0%
o	1	12.5%
n	1	12.5%
g	1	12.5%
l	1	12.5%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1492	66.8%
Common	743	33.2%

Most frequent Common characters

Value	Count	Frequency (%)
	743	100.0%

Most frequent Latin characters

Value	Count	Frequency (%)
A	382	25.6%
C	200	13.4%
M	158	10.6%
N	142	9.5%
Y	78	5.2%
I	74	5.0%
L	69	4.6%
T	56	3.8%
D	54	3.6%
V	41	2.7%
O	38	2.5%
P	33	2.2%
W	31	2.1%
X	28	1.9%
J	17	1.1%
F	16	1.1%
H	14	0.9%
E	10	0.7%
U	10	0.7%
K	9	0.6%
Z	9	0.6%
G	6	0.4%
R	5	0.3%
S	4	0.3%
s	2	0.1%
Other values (5)	6	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2235	100.0%

Most frequent ASCII characters

Value	Count	Frequency (%)
	743	33.2%
A	382	17.1%
C	200	8.9%
M	158	7.1%
N	142	6.4%
Y	78	3.5%
I	74	3.3%
L	69	3.1%
T	56	2.5%
D	54	2.4%
V	41	1.8%
O	38	1.7%
P	33	1.5%
W	31	1.4%
X	28	1.3%
J	17	0.8%
F	16	0.7%
H	14	0.6%
E	10	0.4%
U	10	0.4%
K	9	0.4%
Z	9	0.4%
G	6	0.3%
R	5	0.2%
S	4	0.2%
Other values (6)	8	0.4%

same_state
Boolean

Distinct count	2
Unique (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

1	414
0	328

Frequency Table

Value	Count	Frequency (%)
1	414	55.8%
0	328	44.2%

age
Real number (ℝ)

Distinct count	102
Unique (%)	13.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	46.591644204851754
Minimum	-1
Maximum	276
Zeros	0
Zeros (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	-1
5-th percentile	-1
Q1	11
median	24
Q3	59
95-th percentile	169
Maximum	276
Range	277
Interquartile range (IQR)	48

Descriptive statistics

Standard deviation	53.77881512
Coefficient of variation (CV)	1.154258795
Kurtosis	2.791116976
Mean	46.5916442
Median Absolute Deviation (MAD)	17
Skewness	1.78661821
Sum	34571
Variance	2892.160956

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
-1	50	6.7%
10	32	4.3%
12	31	4.2%
24	27	3.6%
14	24	3.2%
8	21	2.8%
9	19	2.6%
62	18	2.4%
18	18	2.4%
36	18	2.4%
13	18	2.4%
5	16	2.2%
7	15	2.0%
169	14	1.9%
145	14	1.9%
23	14	1.9%
239	14	1.9%
6	13	1.8%
55	12	1.6%
21	12	1.6%
3	12	1.6%
85	10	1.3%
20	10	1.3%
108	10	1.3%
17	10	1.3%
Other values (77)	290	39.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1	50	6.7%
1	2	0.3%
3	12	1.6%
4	5	0.7%
5	16	2.2%
6	13	1.8%
7	15	2.0%
8	21	2.8%
9	19	2.6%
10	32	4.3%

Value	Count	Frequency (%)
276	1	0.1%
239	14	1.9%
208	1	0.1%
190	4	0.5%
174	2	0.3%
171	7	0.9%
170	1	0.1%
169	14	1.9%
168	5	0.7%
164	2	0.3%

python_yn
Boolean

Distinct count	2
Unique (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

1	392
0	350

Frequency Table

Value	Count	Frequency (%)
1	392	52.8%
0	350	47.2%

R_yn
Boolean

Distinct count	2
Unique (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

0	740
1	2

Frequency Table

Value	Count	Frequency (%)
0	740	99.7%
1	2	0.3%

spark
Boolean

Distinct count	2
Unique (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

0	575
1	167

Frequency Table

Value	Count	Frequency (%)
0	575	77.5%
1	167	22.5%

aws
Boolean

Distinct count	2
Unique (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

0	566
1	176

Frequency Table

Value	Count	Frequency (%)
0	566	76.3%
1	176	23.7%

excel
Boolean

Distinct count	2
Unique (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

1	388
0	354

Frequency Table

Value	Count	Frequency (%)
1	388	52.3%
0	354	47.7%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Count
Matrix

First rows

	Job Title	Rating	Location	Headquarters	Size	Founded	Type of ownership	Industry	Sector	Revenue	Competitors	min_salary	max_salary	avg_salary	company_txt	job_state	same_state	age	python_yn	spark	aws	excel
0	Data Scientist	3.8	Albuquerque, NM	Goleta, CA	501 to 1000 employees	1973	Company - Private	Aerospace & Defense	Aerospace & Defense	$50 to $100 million (USD)	-1	53	91	72.0	Tecolote Research\n	NM	0	47	1	0	0	1
1	Healthcare Data Scientist	3.4	Linthicum, MD	Baltimore, MD	10000+ employees	1984	Other Organization	Health Care Services & Hospitals	Health Care	$2 to $5 billion (USD)	-1	63	112	87.5	University of Maryland Medical System\n	MD	0	36	1	0	0	0
2	Data Scientist	4.8	Clearwater, FL	Clearwater, FL	501 to 1000 employees	2010	Company - Private	Security Services	Business Services	$100 to $500 million (USD)	-1	80	90	85.0	KnowBe4\n	FL	1	10	1	1	0	1
3	Data Scientist	3.8	Richland, WA	Richland, WA	1001 to 5000 employees	1965	Government	Energy	Oil, Gas, Energy & Utilities	$500 million to $1 billion (USD)	Oak Ridge National Laboratory, National Renewable Energy Lab, Los Alamos National Laboratory	56	97	76.5	PNNL\n	WA	1	55	1	0	0	0
4	Data Scientist	2.9	New York, NY	New York, NY	51 to 200 employees	1998	Company - Private	Advertising & Marketing	Business Services	Unknown / Non-Applicable	Commerce Signals, Cardlytics, Yodlee	86	143	114.5	Affinity Solutions\n	NY	1	22	1	0	0	1
5	Data Scientist	3.4	Dallas, TX	Dallas, TX	201 to 500 employees	2000	Company - Public	Real Estate	Real Estate	$1 to $2 billion (USD)	Digital Realty, CoreSite, Equinix	71	119	95.0	CyrusOne\n	TX	1	20	1	0	1	1
6	Data Scientist	4.1	Baltimore, MD	Baltimore, MD	501 to 1000 employees	2008	Company - Private	Banks & Credit Unions	Finance	Unknown / Non-Applicable	-1	54	93	73.5	ClearOne Advantage\n	MD	1	12	0	0	0	1
7	Data Scientist	3.8	San Jose, CA	Seattle, WA	201 to 500 employees	2005	Company - Private	Consulting	Business Services	$25 to $50 million (USD)	-1	86	142	114.0	Logic20/20\n	CA	0	15	1	1	1	1
8	Research Scientist	3.3	Rochester, NY	Rochester, NY	10000+ employees	2014	Hospital	Health Care Services & Hospitals	Health Care	$500 million to $1 billion (USD)	-1	38	84	61.0	Rochester Regional Health\n	NY	1	6	0	0	0	0
9	Data Scientist	4.6	New York, NY	New York, NY	51 to 200 employees	2009	Company - Private	Internet	Information Technology	$100 to $500 million (USD)	Clicktripz, SmarterTravel	120	160	140.0	<intent>\n	NY	1	11	1	1	0	0

Last rows

	Job Title	Rating	Location	Headquarters	Size	Founded	Type of ownership	Industry	Sector	Revenue	Competitors	min_salary	max_salary	avg_salary	company_txt	job_state	same_state	age	python_yn	spark	aws	excel
732	Machine Learning Engineer (NLP)	4.1	Palo Alto, CA	Palo Alto, CA	1 to 50 employees	2007	Company - Private	K-12 Education	Education	Unknown / Non-Applicable	-1	80	142	111.0	CK-12 Foundation\n	CA	1	13	1	0	1	1
733	Senior Data Analyst	3.9	San Francisco, CA	San Francisco, CA	51 to 200 employees	2008	Company - Public	Computer Hardware & Software	Information Technology	Unknown / Non-Applicable	-1	99	178	138.5	Life360\n	CA	1	12	1	0	0	0
734	Data Science Project Manager	3.6	Boston, MA	Springfield, MA	5001 to 10000 employees	1851	Company - Private	Insurance Carriers	Insurance	$10+ billion (USD)	-1	37	100	68.5	MassMutual\n	MA	0	169	0	0	0	1
735	Data Engineer	3.9	San Francisco, CA	San Francisco, CA	201 to 500 employees	2011	Company - Private	Internet	Information Technology	$100 to $500 million (USD)	Belly, SpotOn	62	113	87.5	Fivestars\n	CA	1	9	1	0	1	1
736	Principal, Data Science - Advanced Analytics	3.6	Plymouth Meeting, PA	Durham, NC	10000+ employees	2017	Company - Public	Biotech & Pharmaceuticals	Biotech & Pharmaceuticals	$2 to $5 billion (USD)	PPD, INC Research, PRA Health Sciences	86	137	111.5	IQVIA\n	PA	0	3	0	0	0	0
737	Sr Scientist, Immuno-Oncology - Oncology	3.9	Cambridge, MA	Brentford, United Kingdom	10000+ employees	1830	Company - Public	Biotech & Pharmaceuticals	Biotech & Pharmaceuticals	$10+ billion (USD)	Pfizer, AstraZeneca, Merck	58	111	84.5	GSK\n	MA	0	190	0	0	1	0
738	Senior Data Engineer	4.4	Nashville, TN	San Francisco, CA	1001 to 5000 employees	2006	Company - Public	Internet	Information Technology	$100 to $500 million (USD)	See Tickets, TicketWeb, Vendini	72	133	102.5	Eventbrite\n	TN	0	14	1	1	1	0
739	Project Scientist - Auton Lab, Robotics Institute	2.6	Pittsburgh, PA	Pittsburgh, PA	501 to 1000 employees	1984	College / University	Colleges & Universities	Education	Unknown / Non-Applicable	-1	56	91	73.5	Software Engineering Institute\n	PA	1	36	0	0	0	1
740	Data Science Manager	3.2	Allentown, PA	Chadds Ford, PA	1 to 50 employees	-1	Company - Private	Staffing & Outsourcing	Business Services	$5 to $10 million (USD)	-1	95	160	127.5	Numeric, LLC\n	PA	0	-1	0	0	0	1
741	Research Scientist – Security and Privacy	3.6	Beavercreek, OH	Arlington, VA	501 to 1000 employees	1967	Nonprofit Organization	Federal Agencies	Government	$50 to $100 million (USD)	-1	61	126	93.5	Riverside Research Institute\n	OH	0	53	1	0	0	0

Most frequent

	Job Title	Rating	Location	Headquarters	Size	Founded	Type of ownership	Industry	Sector	Revenue	Competitors	hourly	min_salary	max_salary	avg_salary	company_txt	job_state	same_state	age	python_yn	aws	excel	count
2	Analytics Manager - Data Mart	3.5	Scotts Valley, CA	Scotts Valley, CA	501 to 1000 employees	1996	Nonprofit Organization	Health Care Services & Hospitals	Health Care	$500 million to $1 billion (USD)	-1	0	42	86	64.0	Central California Alliance for Health\n	CA	1	24	0	0	0	4
95	Food Scientist - Developer	3.3	Milwaukee, WI	Milwaukee, WI	501 to 1000 employees	1964	Company - Private	Food & Beverage Manufacturing	Manufacturing	Unknown / Non-Applicable	-1	0	40	68	54.0	Palermo's Pizza\n	WI	1	56	0	0	0	4
108	MED TECH/LAB SCIENTIST- SOUTH COASTAL LAB	3.6	Millville, DE	Lewes, DE	1001 to 5000 employees	1935	Nonprofit Organization	Health Care Services & Hospitals	Health Care	$100 to $500 million (USD)	-1	1	21	34	27.5	Beebe Healthcare\n	DE	0	85	0	0	0	4
115	Marketing Data Analyst	3.6	Highland, CA	Highland, CA	1001 to 5000 employees	1986	Company - Private	Gambling	Arts, Entertainment & Recreation	$100 to $500 million (USD)	-1	0	35	62	48.5	San Manuel Casino\n	CA	1	34	0	0	1	4
120	Medical Laboratory Scientist	4.0	Burleson, TX	Arlington, TX	1001 to 5000 employees	1977	Hospital	Health Care Services & Hospitals	Health Care	$50 to $100 million (USD)	-1	1	18	25	21.5	Texas Health Huguley Hospital\n	TX	0	43	0	1	0	4
136	R&D Specialist/ Food Scientist	2.4	Hoopeston, IL	Flower Mound, TX	501 to 1000 employees	-1	Company - Private	Food & Beverage Manufacturing	Manufacturing	$100 to $500 million (USD)	-1	0	39	66	52.5	Teasdale Latin Foods\n	IL	0	-1	0	0	0	4
188	Senior Research Scientist-Machine Learning	2.6	Pittsburgh, PA	Pittsburgh, PA	501 to 1000 employees	1984	College / University	Colleges & Universities	Education	Unknown / Non-Applicable	-1	0	81	167	124.0	Software Engineering Institute\n	PA	1	36	0	0	0	4
205	Sr. Data Engineer - Contract-to-Hire (Java)	3.0	Knoxville, TN	Knoxville, TN	10000+ employees	1958	Company - Private	Gas Stations	Retail	$10+ billion (USD)	TravelCenters of America, Love's Travel Stops & Country Stores, Wawa	0	69	127	98.0	Pilot Flying J Travel Centers LLC\n	TN	1	62	1	0	0	4
217	Staff Scientist-Downstream Process Development	2.7	Rockville, MD	Rockville, MD	201 to 500 employees	1961	Company - Private	Biotech & Pharmaceuticals	Biotech & Pharmaceuticals	$25 to $50 million (USD)	-1	0	49	113	81.0	Advanced BioScience Laboratories\n	MD	1	59	0	0	1	4
3	Associate Data Analyst- Graduate Development Program	3.3	Richfield, OH	Richfield, OH	501 to 1000 employees	1989	Company - Private	Insurance Carriers	Insurance	$500 million to $1 billion (USD)	-1	0	32	59	45.5	National Interstate\n	OH	1	31	0	0	0	3

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent Uppercase Letter characters

Most frequent Lowercase Letter characters

Most frequent Space Separator characters

Most frequent Dash Punctuation characters

Most frequent Other Punctuation characters

Most frequent Decimal Number characters

Most frequent Open Punctuation characters

Most frequent Close Punctuation characters

Most frequent Math Symbol characters

Most occurring scripts

Most frequent Latin characters

Most frequent Common characters

Most occurring blocks

Most frequent ASCII characters

Most frequent Punctuation characters

Most occurring characters

Most occurring categories

Most frequent Uppercase Letter characters

Most frequent Lowercase Letter characters

Most frequent Other Punctuation characters

Most frequent Space Separator characters

Most frequent Dash Punctuation characters

Most occurring scripts

Most frequent Latin characters

Most frequent Common characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Uppercase Letter characters

Most frequent Lowercase Letter characters

Most frequent Other Punctuation characters

Most frequent Space Separator characters

Most frequent Dash Punctuation characters

Most frequent Decimal Number characters

Most occurring scripts

Most frequent Latin characters

Most frequent Common characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Decimal Number characters

Most frequent Space Separator characters

Most frequent Lowercase Letter characters

Most frequent Math Symbol characters

Most frequent Uppercase Letter characters

Most frequent Dash Punctuation characters

Most occurring scripts

Most frequent Common characters

Most frequent Latin characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Uppercase Letter characters

Most frequent Lowercase Letter characters

Most frequent Space Separator characters

Most frequent Dash Punctuation characters

Most frequent Other Punctuation characters

Most frequent Decimal Number characters

Most occurring scripts

Most frequent Latin characters

Most frequent Common characters

Most occurring blocks

Most frequent ASCII characters

Most occurring characters

Most occurring categories

Most frequent Uppercase Letter characters

Most frequent Lowercase Letter characters

Most frequent Space Separator characters

Most frequent Other Punctuation characters

Most frequent Dash Punctuation characters

Most frequent Decimal Number characters

Most occurring scripts

Most frequent Latin characters